Mark Alber - Academia.edu (original) (raw)

Papers by Mark Alber

Bulletin of the American Physical Society, 2018

Current Opinion in Biomedical Engineering, 2022

Fibrin deformation and interaction of fibrin with other blood components play critical roles in h... more Fibrin deformation and interaction of fibrin with other blood components play critical roles in hemostasis and thrombosis. In this review, computational and mathematical biomechanical models of fibrin network deformation and contraction at different spatio-temporal scales as well as challenges in developing and calibrating multiscale models are discussed. There are long standing challenges. For instance, applicability of models to identify and test potential mechanisms of the biomechanical processes mediating interactions between platelets and fiber networks in blood clot stretching and contraction needs to be examined carefully. How the structural and mechanical properties of major blood clot components influences biomechanical responses of the entire clot subjected to external forces, such as blood flow or vessel wall deformations needs to be investigated thoroughly.

ABSTRACTExperimental measurements or computational model predictions of the post-translational re... more ABSTRACTExperimental measurements or computational model predictions of the post-translational regulation of enzymes needed in a metabolic pathway is a difficult problem. Consequently, regulation is mostly known only for well-studied reactions of central metabolism in various model organisms. In this study, we utilize two approaches to predict enzyme regulation policies and investigate the hypothesis that regulation is driven by the need to maintain the solvent capacity in the cell. The first predictive method uses a statistical thermodynamics and metabolic control theory framework while the second method is performed using a hybrid optimization-reinforcement learning approach. Efficient regulation schemes were learned from experimental data that either agree with theoretical calculations or result in a higher cell fitness using maximum useful work as a metric. Model predictions provide the following novel general principles: (1) the regulation itself causes the reactions to be much...

Journal of The Royal Society Interface, 2020

Experimental measurements or computational model predictions of the post-translational regulation... more Experimental measurements or computational model predictions of the post-translational regulation of enzymes needed in a metabolic pathway is a difficult problem. Consequently, regulation is mostly known only for well-studied reactions of central metabolism in various model organisms. In this study, we use two approaches to predict enzyme regulation policies and investigate the hypothesis that regulation is driven by the need to maintain the solvent capacity in the cell. The first predictive method uses a statistical thermodynamics and metabolic control theory framework while the second method is performed using a hybrid optimization–reinforcement learning approach. Efficient regulation schemes were learned from experimental data that either agree with theoretical calculations or result in a higher cell fitness using maximum useful work as a metric. As previously hypothesized, regulation is herein shown to control the concentrations of both immediate and downstream product concentra...

Oncogene, 2017

During epithelial ovarian cancer (EOC) progression, intraperitoneally disseminating tumor cells a... more During epithelial ovarian cancer (EOC) progression, intraperitoneally disseminating tumor cells and multi-cellular aggregates (MCAs) present in ascites fluid adhere to the peritoneum and induce retraction of the peritoneal mesothelial monolayer prior to invasion of the collagen-rich submesothelial matrix and proliferation into macro-metastases. Clinical studies have shown heterogeneity among EOC metastatic units with respect to cadherin expression profiles and invasive behavior, however the impact of distinct cadherin profiles on peritoneal anchoring of metastatic lesions remains poorly understood. In the current study, we demonstrate that metastasisassociated behaviors of ovarian cancer cells and MCAs are influenced by cellular cadherin composition. Our results show that mesenchymal N-cadherin expressing (Ncad+) cells and MCAs invade much more efficiently than E-cadherin expressing (Ecad+) cells. Ncad+ MCAs exhibit rapid lateral dispersal prior to penetration of three-dimensional collagen matrices. When seeded as individual cells, lateral migration and cell-cell junction formation precede matrix invasion. Neutralizing the Ncad extracellular domain with the monoclonal antibody GC-4 suppresses lateral dispersal and cell penetration of collagen gels. In contrast, use of a broad spectrum matrix metalloproteinase (MMP) inhibitor (GM6001) to block endogenous membrane type 1 matrix metalloproteinase (MT1-MMP) activity does not fully inhibit cell invasion. Using intact tissue Users may view, print, copy, and download text and data-mine the content in such documents, for the purposes of academic research, subject always to the full Conditions of use:

Journal of biomechanics, Jan 4, 2017

A novel multi-component model is introduced for studying interaction between blood flow and defor... more A novel multi-component model is introduced for studying interaction between blood flow and deforming aortic wall with intramural hematoma (IMH). The aortic wall is simulated by a composite structure submodel representing material properties of the three main wall layers. The IMH is described by a poroelasticity submodel which takes into account both the pressure inside hematoma and its deformation. The submodel of the hematoma is fully coupled with the aortic submodel as well as with the submodel of the pulsatile blood flow. Model simulations are used to investigate the relation between the peak wall stress, hematoma thickness and permeability in patients of different age. The results indicate that an increase in hematoma thickness leads to larger wall stress, which is in agreement with clinical data. Further simulations demonstrate that a hematoma with smaller permeability results in larger wall stress, suggesting that blood coagulation in hematoma might increase its mechanical st...

Biophysical Journal, 2016

assembly of amyloid-forming peptides into nanosheets as a retrovirus carrier. PNAS, 2015

Lecture Notes in Computer Science, 2014

Tracking the motion of Myxococcus xanthus is a crucial step for fundamental bacteria studies. Lar... more Tracking the motion of Myxococcus xanthus is a crucial step for fundamental bacteria studies. Large number of bacterial cells involved, limited image resolution, and various cell behaviors (e.g., division) make tracking a highly challenging problem. A common strategy is to segment the cells first and associate detected cells into moving trajectories. However, known detection association algorithms that run in polynomial time are either ineffective to deal with particular cell behaviors or sensitive to segmentation errors. In this paper, we propose a polynomial time hierarchical approach for associating segmented cells, using a new Earth Mover's Distance (EMD) based matching model. Our method is able to track cell motion when cells may divide, leave/enter the image window, and the segmentation results may incur false alarm, detection lost, and falsely merged/split detections. We demonstrate it on tracking M. xanthus. Applied to error-prone segmented cells, our algorithm exhibits higher track purity and produces more complete trajectories, comparing to several state-of-the-art detection association algorithms.

(A-A″) Calibration test to determine parameters for cell elasticity, analogous to experi... more (A-A″) Calibration test to determine parameters for cell elasticity, analogous to experimental single cell stretching tests [<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1005533#pcbi.1005533.ref066" target="_blank">66</a>], (A) Initial condition t = 0, (A′) 6 minutes after simulation with no force applied, (A″) after 72 minutes cell is completely on tension (B-B″) Cell adhesivity test, analogous to experimental tests [<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1005533#pcbi.1005533.ref069" target="_blank">69</a>] for calibrating the level of cell-cell adhesion between adjacent cells. (B) Initial condition t = 0, (B′) 6 minutes after simulation begins with no force applied, (B″) after 72 minutes, 15 nN force is applied. (C) Stress versus strain for single cell calibration (red line) and stress versus strain for calibrating the level of adhesivity between the two cells (blue line) [<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1005533#pcbi.1005533.ref069" target="_blank">69</a>,<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1005533#pcbi.1005533.ref070" target="_blank">70</a>]. Initial negative strain in adhesivity test is due to strong adhesion between two cells. (D) Force and strain as a function of time for adhesivity test. (E) Tissue growth rate calibration by comparing with the experimental data by Wartlick et al. [<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1005533#pcbi.1005533.ref056" target="_blank">56</a>]. The 95% confidence interval for the growth rate results is shown in grey color.</p

Sensitivity estimation of (A) (Amit<... more Sensitivity estimation of (A) (Amit/Ainter) and (B) Rnorm to small perturbation in the three mitotic parameter set points, , , and ΔP. Sensitivity was estimated from the reduced RSM model described in <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1005533#pcbi.1005533.g007" target="_blank">Fig 7C–7F</a> after stepwise model regression (p-value cutoff of 0.01). (C) Proposed mechanical regulatory network defined for “physiological ranges” within the parameter ranges defined by the CCD (Run 2, <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1005533#pcbi.1005533.g007" target="_blank">Fig 7A</a>) that summarizes the local sensitivity analysis. Cell adhesivity, an increase in , slightly inhibits area expansion and strongly inhibits roundness. Membrane stiffness, inhibits area expansion and promotes roundness. Mitotic area expansion is most sensitive to variation in the mitotic pressure change (ΔP), but pressure has little effect on roundness over the calibrated physiological ranges.</p

A recently proposed mathematical model of a "core" set of cellular and molecular interactions pre... more A recently proposed mathematical model of a "core" set of cellular and molecular interactions present in the developing vertebrate limb was shown to exhibit patternforming instabilities and limb skeleton-like patterns under certain restrictive conditions, suggesting that it may authentically represent the underlying embryonic process (Hentschel et al., 2004). The model, an eight-equation system of partial differential equations, incorporates the behavior of mesenchymal cells as "reactors," both participating in the generation of morphogen patterns and changing their state and position in response to them. The full system, which has smooth solutions that exist globally in time, is nonetheless highly complex and difficult to handle analytically or numerically. According to a recent classification of developmental mechanisms (Salazar-Ciudad et al., 2003), the limb model of Hentschel et al. (2004) is "morphodynamic," since differentiation of new cell types occurs simultaneously with cell rearrangement. This contrasts with "morphostatic" mechanisms, in which cell identity becomes established independently of cell rearrangement. Under the hypothesis that development of some vertebrate limbs employs the core mechanism in a morphostatic fashion, we derive in an analytically rigorous fashion a pair of equations representing the spatiotemporal evolution of the morphogen fields under the assumption that cell differentiation relaxes faster than the evolution of the overall cell density (i.e., the morphostatic limit of the full system). This simple reaction-diffusion system is unique in having been derived in an analytically rigorous fashion from a substantially more complex system involving multiple morphogens, extracellular matrix deposition, haptotaxis, and cell translocation. We identify regions in the parameter space of the reduced system where Turing-type pattern formation is possible, which we refer to as its "Turing space." Obtained values of the parameters are used in numerical simulations of the reduced system, using a new Galerkin finite element method, in tissue domains with nonstandard geometry. The reduced system exhibits patterns of spots and stripes like those seen in developing limbs, indicating its potential utility in hybrid continuum-discrete stochastic modeling of limb development. Lastly, we discuss the possible role in limb evolution of selection for increasingly morphostatic developmental mechanisms.

In this paper we present the foundation of a unified, object-oriented, three-dimensional (3D) bio... more In this paper we present the foundation of a unified, object-oriented, three-dimensional (3D) biomodeling environment, which allows us to integrate multiple submodels at scales from subcellular to tissues and organs. Our current implementation combines a modified discrete model from statistical mechanics, the Cellular Potts Model (CPM), with a continuum reaction-diffusion (RD) model and a state automaton with well-defined conditions for cell differentiation transitions to model genetic regulation. This environment allows us to rapidly and compactly create computational models of a class of complex developmental phenomena. To illustrate model development, we simulate a simplified version of the formation of the skeletal pattern in a growing embryonic vertebrate limb.

Structural and mechanical properties of fibrin networks, which are essential factors determining ... more Structural and mechanical properties of fibrin networks, which are essential factors determining growth and stability of blood clots, can dynamically undergo fast changes due to blood flow shear, clot contraction, or vasospasms. Predicting these alterations using computational modeling is important for understanding mechanisms governing clot deformation under various (patho-)physiological conditions and designing new fibrin-based bio-materials. In this work, a discrete worm-like-chain model (WLC) of a fibrin network is introduced to study how the macroscale behavior of the network, including macro-scale structural changes and force-strain response of the fibrin clot, emerge from the micro-scale characteristics of the network. The model was calibrated using confocal microscopy data on single fiber stretching and the simulation results will be shown to be in good agreement with the data obtained in the fibrin gel stretching experiments. Additionally, simulations demonstrate how structural metrics, such as length and orientation of individual fibers, change when stretching forces are applied to the network and how network's stress-strain response depends on these metrics. Lastly, the addition of a modeling component representing bending of single fibers, allowed us to study impacts of shear stress and compression on the network and how its stress-strain profile under these conditions depends on bending stiffness and other properties of the network. The suggested micro-scale mechanisms based on alignment and bending of fibers, tested in simulations, are used to make predictions about the behavior of the fibrin network under patient specific conditions.

The Cellular Potts Model (CPM) has been used at a cellular scale for simulating various biologica... more The Cellular Potts Model (CPM) has been used at a cellular scale for simulating various biological phenomena such as differential adhesion, fruiting body formation of the slime mold Dictyostelium discoideum, angiogenesis, cancer invasion, chondrogenesis in embryonic vertebrate limbs, and many others. Continuous models in the form of partial differential, integral or integro-differential equations are used for studying biological problems at large scale. It is crucial for developing multi-scale biological models to establish a connection between discrete stochastic models, including CPM, and continuous models. To demonstrate multiscale approach we derive in this paper continuous limit of a two dimensional CPM with the chemotactic interactions in the form of a Fokker-Planck equation describing evolution of the cell probability density function. This equation is then reduced to the classical macroscopic Keller-Segel model. Theoretical results are verified numerically by comparing Monte...

Nature Communications, 2021

Regulation of the homeodomain transcription factor WUSCHEL concentration is critical for stem cel... more Regulation of the homeodomain transcription factor WUSCHEL concentration is critical for stem cell homeostasis in Arabidopsis shoot apical meristems. WUSCHEL regulates the transcription of CLAVATA3 through a concentration-dependent activation-repression switch. CLAVATA3, a secreted peptide, activates receptor kinase signaling to repress WUSCHEL transcription. Considering the revised regulation, CLAVATA3 mediated repression of WUSCHEL transcription alone will lead to an unstable system. Here we show that CLAVATA3 signaling regulates nuclear-cytoplasmic partitioning of WUSCHEL to control nuclear levels and its diffusion into adjacent cells. Our work also reveals that WUSCHEL directly interacts with EXPORTINS via EAR-like domain which is also required for destabilizing WUSCHEL in the cytoplasm. We develop a combined experimental and computational modeling approach that integrates CLAVATA3-mediated transcriptional repression of WUSCHEL and post-translational control of nuclear levels wi...

The budding yeast,Saccharomyces cerevisiae, is a prime biological model to study mechanisms under... more The budding yeast,Saccharomyces cerevisiae, is a prime biological model to study mechanisms underlying asymmetric growth. Previous studies have shown that, prior to yeast bud emergence, polarization of a conserved small GTPase, Cdc42, must be established. Additionally, hydrolase changes the mechanical properties of the cell wall and plasma membrane with the periplasm between them (cell surface). However, how the surface mechanical properties in the emerging bud are different from the properties of the mother cell and their role in bud formation are not well understood. We hypothesize that the polarized chemical signal alters the local dimensionless ratio of stretching to bending stiffness of the cell surface of the emerging yeast bud. To test this hypothesis, a novel three-dimensional coarse-grained particle-based model has been developed which describes inhomogeneous mechanical properties of the cell surface. Model simulations suggest that regulation of the dimensionless ratio of s...

Archives of Computational Methods in Engineering, 2020

Machine learning is increasingly recognized as a promising technology in the biological, biomedic... more Machine learning is increasingly recognized as a promising technology in the biological, biomedical, and behavioral sciences. There can be no argument that this technique is incredibly successful in image recognition with immediate applications in diagnostics including electrophysiology, radiology, or pathology, where we have access to massive amounts of annotated data. However, machine learning often performs poorly in prognosis, especially when dealing with sparse data. This is a field where classical physics-based simulation seems to remain irreplaceable. In this review, we identify areas in the biomedical sciences where machine learning and multiscale modeling can mutually benefit from one another: Machine learning can integrate physics-based knowledge in the form of governing equations, boundary conditions, or constraints to manage ill-posted problems and robustly handle sparse and noisy data; multiscale modeling can integrate machine learning to create surrogate models, identify system dynamics and parameters, analyze sensitivities, and quantify uncertainty to bridge the scales and understand the emergence of function. With a view towards applications in the life sciences, we discuss the state of the art of combining machine learning and multiscale modeling, identify applications and opportunities, raise open questions, and address potential challenges and limitations. This review serves as introduction to a special issue on Uncertainty Quantification, Machine Learning, and Data-Driven Modeling of Biological Systems that will help identify current roadblocks and areas where computational mechanics, as a discipline, can play a significant role. We anticipate that it will stimulate discussion within the community of computational mechanics and reach out to other disciplines including mathematics, statistics, computer science, artificial intelligence, biomedicine, systems biology, and precision medicine to join forces towards creating robust and efficient models for biological systems.